Google Gemini: The New Generative AI Platform in 2024

30 June 202411 July 2024 usnewsgist.com 80 Views 0 Comments 6 min read

Google is aiming to create a splash with Gemini, its leading collection of generative AI models, applications, and services.

What exactly is Google Gemini? How can it be utilized? And how does Gemini compare with its competitors?

To facilitate staying current with the latest Gemini advancements, we’ve compiled this convenient guide, which will be continually updated with new models, features, and updates on Google’s strategies for Gemini.

What is Gemini?

Gemini is Google’s latest generation of generative AI models, developed jointly by DeepMind and Google Research. It includes four variations:

– Gemini Ultra, the highest-performing model in the Gemini family.

– Gemini Pro, a lighter version designed for efficiency.

– Gemini Flash, a faster and distilled version of Pro.

– Gemini Nano, consisting of two small models, Nano-1 and Nano-2, optimized to run offline on mobile devices.

Unlike Google’s LaMDA, which focuses exclusively on text data, Gemini models are multimodal, capable of processing and analyzing audio, images, videos, codebases, and text in various languages. They have been trained extensively on a mix of public, proprietary, and licensed data.

It’s important to consider ethical and legal implications when using models like Gemini, especially concerning data ownership and consent issues. Google has policies in place to address legal risks for certain Google Cloud customers, but these policies may have limitations and exceptions.

Gemini in Gmail, Docs, Chrome, dev tools and more

Gemini models are not limited to dedicated Gemini apps for accessing their assistance. They are gradually integrating into core Google services such as Gmail and Google Docs.

To access most of these features, users will need the Google One AI Premium Plan, priced at $20. This plan integrates Gemini into Google Workspace apps like Docs, Slides, Sheets, and Meet. It also includes Gemini Advanced, which incorporates Gemini Ultra for enhanced capabilities, such as analyzing and answering questions about uploaded files.

Gemini Advanced subscribers enjoy additional features, including trip planning through Google Search, which generates personalized travel itineraries based on user inputs. It considers details like flight schedules from Gmail, meal preferences, local attractions from Google Search and Maps, and distances between locations. The itinerary updates automatically to reflect any changes.

In Gmail, Gemini resides in a sidebar that assists in composing emails and summarizing message threads. Similarly, in Docs, it aids in writing, refining content, and brainstorming ideas. In Slides, Gemini generates slides and custom images, while in Google Sheets, it manages data by creating tables and formulas.

Gemini also extends its functionality to Google Drive, where it can summarize files and provide quick project insights. In Google Meet, Gemini translates captions into multiple languages to facilitate multilingual communication.

Gemini has expanded its presence across various Google products beyond dedicated apps, including integration into Google’s Chrome browser as an AI writing tool. This tool allows users to create new content or rewrite existing text, leveraging insights from the current webpage for personalized recommendations.

Beyond Chrome, Gemini’s influence extends to Google’s database solutions, cloud security tools, and app development platforms like Firebase and Project IDX. It also contributes to consumer-facing applications such as Google TV, where it generates descriptions for movies and TV shows, and Google Photos, where it supports natural language search queries. Additionally, Gemini powers the NotebookLM note-taking assistant.

In the realm of software development, Gemini plays a pivotal role in Code Assist (formerly known as Duet AI for Developers), a suite of AI-driven tools for code completion and generation. It also enhances Google’s security offerings, including Gemini in Threat Intelligence, which analyzes potentially malicious code segments and enables users to conduct natural language searches for ongoing threats or signs of compromise.

Custom chatbots powered by Gemini Gems

At Google I/O 2024, Google announced that Gemini Advanced users will soon have the ability to create Gems, personalized chatbots powered by Gemini models. These Gems can be generated based on natural language descriptions such as “Act as my running coach and provide daily running plans.” Users will have the option to share these Gems with others or keep them private.

In the future, Gems will gain access to a broader range of integrations with Google services, including Google Calendar, Tasks, Keep, and YouTube Music, enabling them to perform a variety of tasks seamlessly.

Gemini Live offers detailed voice conversations

Gemini Live, a new feature exclusive to Gemini Advanced subscribers, will soon debut on the Gemini mobile apps, offering users an interactive voice chat experience. With Gemini Live activated, users can interrupt Gemini during conversations to ask questions for clarification, and the chatbot will adjust its responses based on the user’s speech patterns in real time. Additionally, Gemini will have the capability to view and respond to users’ surroundings using photos or video captured by their smartphone cameras.

The Live feature is also designed to function as a virtual coach, assisting users in rehearsing for events and brainstorming ideas. For example, it can provide suggestions on which skills to emphasize during upcoming job interviews or internships, and offer advice on public speaking.

What can the Gemini models do?

Assuming Google’s recent assertions are accurate, Gemini models are capable of performing a wide array of multimodal tasks, including speech transcription and real-time captioning of images and videos. Many of these functionalities have already been implemented in products, as mentioned earlier, and Google promises further advancements in the near future.

However, skepticism persists given Google’s track record. The initial Bard launch fell short of expectations, and a recent video showcasing Gemini’s capabilities was more aspirational than reflective of live performance. Additionally, an image generation feature proved to be notably inaccurate.

Moreover, Google has not addressed fundamental issues plaguing generative AI, such as encoded biases and tendencies to fabricate information. While competitors face similar challenges, these concerns are significant for anyone considering adoption or investment in Gemini.

Assuming Google’s recent claims are credible, here’s a summary of what the current tiers of Gemini can achieve and their potential capabilities once fully developed:

What you can do with Gemini Ultra

Google describes Gemini Ultra as a highly capable multimodal AI model designed to assist with tasks such as solving physics homework step-by-step, identifying errors in completed answers, and extracting relevant information from scientific papers. This model can update charts with current data by generating necessary formulas based on information extracted from multiple papers.

While Gemini Ultra technically supports image generation, this feature has not yet been integrated into the model’s productized version, possibly due to its complexity compared to how other applications generate images. Instead of using an intermediary step like prompting an image generator, Gemini Ultra outputs images directly.

Access to Gemini Ultra is available through Google’s Vertex AI and AI Studio platforms, as well as through Gemini apps, but requires a subscription to the AI Premium Plan.

Gemini Pro’s capabilities

Gemini Pro, specifically Gemini 1.5 Pro, is positioned by Google as an advancement over its predecessor, LaMDA, particularly in reasoning, planning, and understanding capabilities. It can process large volumes of data, including up to 1.4 million words, two hours of video, or 22 hours of audio, and can reason across or answer questions about this data.

Released in June on Vertex AI and AI Studio, Gemini 1.5 Pro includes a feature called code execution aimed at refining code generated by the model iteratively to reduce bugs. This capability also extends to Gemini Flash.

Developers using Vertex AI can customize Gemini Pro for specific contexts and use cases through a grounding process. This includes integrating data from third-party providers like Moody’s, Thomson Reuters, ZoomInfo, and MSCI, or using corporate datasets and Google Search for information retrieval. Gemini Pro can also interact with external APIs to automate workflows and perform specific tasks.

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